基于非对称GARCH与极值理论的商业银行信用风险度量模型

提出一种基于ARMA-TGARCH-EVT模型并适用于商业银行内部信用风险评估的新方法.首先通过广义矩法估计ARMA-TGARCH模型,获得近似独立同分布的残差序列zt;然后选用极值理论的越槛高峰模型(POT)对残差序列进行拟合分析,得到风险价值和期望损失的估计值,并采用Bootstrap方法给出95%置信水平下的置信区间;最后利用某商业银行2000-02-19～2010-12-15的日信贷资产对数收益率进行仿真,得到控制信用风险价值V和期望损失E值及置信区间,并与未经调整的预测值进行比较.研究结果表明,该方法在一定程度上克服了单纯进行极值分析时,由于序列的非独立同分布不能满足极值理论假设所造成的估计误差,改进了采用似然比率法估计置信区间时,由于极值事件的小样本所造成的偏差.

Model of Credit Risk Assessment in Commercial Banks Based on Asymmetric GARCH and Extreme Value Theory

A new method for evaluating commercial bank's internal credit risk based on ARMA-TGARCH-EVT model is proposed. Firstly, a mixed model of ARMA-TGARCH is estimated using GMM, and then the residual series z_t with properties of approximately independent and identically distribution is obtained. Secondly, the POT model of extreme value theory is employed for fitting analysis of the residual sequence to get the estimated value of VAR and ES, and the Bootstrap method is used to determine the confidence interval of VAR and ES at 95% confidence level. Finally, the data that the daily credit asset's logarithmic yields of a commercial bank from 2000-02-19~2010-12-15 are utilized to simulate the results from using this method. Simulation results indicate that, compared with the unadjusted predictive value, the proposed method could overcome the estimation error to some extent, since the sequence's non-independent-and-identically distribution could not meet the assumptions of extreme value theory. Moreover, the method could improve the deviation caused by small samples of extreme events when the likelihood ratio method is used to estimate confidence intervals.